#GPU performance

'Explore how CUDA, ROCm, Triton and TensorRT map tensor programs to GPU hardware and which compiler-level optimizations yield the biggest performance gains.'

DeepReinforce's CUDA-L1 framework uses Contrastive Reinforcement Learning to automatically optimize CUDA code, achieving an average 3.12× speedup and up to 120× acceleration across diverse GPU workloads.